Eikosstatistics & data science

Programming & Scientific Computing · R Programming & Statistical Analysis

Data Manipulation and Transformation with tidyverse

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction data |> filter (condition) |> mutate (new_var) |> summarise (statistic) Data Science with R · Expert Level

Overview

Topics covered

  • Introduction
  • Tidy Data Philosophy and the tidyverse Ecosystem
  • The Tidy Data Principle (Wickham, 2014)
  • Tidyverse ecosystem architecture
  • The pipe operator: |> (R 4.1+) vs %>% (magrittr)
  • The tibble as a canonical data structure

Related concepts

Main connections

  • Median & robust location
  • Preprocessing pipelines & transform recipes
  • Statistical graphics & visual reasoning
  • Quantiles & percentiles
  • SQL & relational data modeling
  • Mean & expected value

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

x|>f()|>g()|>h()≡h(g(f(x)))
View LaTeX sourcex \;\texttt{|>}\; f() \;\texttt{|>}\; g() \;\texttt{|>}\; h() \;\equiv\; h(g(f(x)))